The present invention generally relates to methods and systems for managing air traffic. More particularly, aspects of this invention include methods and systems for predicting trajectories of aircraft using models that may be adapted via tunable parameters. Those parameters may have direct physical meaning (for example, weight) or they may be abstract, as in the case of the ratio of two physical variables such as the ratio of thrust to mass. Accurate trajectory prediction is key to a number of air traffic control and trajectory management applications, and the ability to infer parameters helps to improve the level of prediction accuracy. The trajectory prediction methods and systems are preferably capable of making use of automation systems of the Air Navigation System Provider (ANSP) or of the Operations Control Center (OCC).
Trajectory-Based Operations (TBO) is a key component of both the US Next Generation Air Transport System (NextGen) and Europe's Single European Sky ATM Research (SESAR). There is a significant amount of effort underway in both programs to advance this concept. Aircraft trajectory synchronization and trajectory negotiation are key capabilities in existing TBO concepts, and provide the framework to improve the efficiency of airspace operations. Trajectory synchronization and negotiation implemented in TBO also enable airspace users (including flight operators (airlines), flight dispatchers, flight deck personnel, Unmanned Aerial Systems, and military users) to regularly fly trajectories close to their preferred (user-preferred) trajectories, enabling business objectives, including fuel and time savings, wind-optimal routing, and direction to go around weather cells, to be incorporated into TBO concepts. As such, there is a desire to generate technologies that support trajectory synchronization and negotiation, which in turn are able to facilitate and accelerate the adoption of TBO.
As used herein, the trajectory of an aircraft is a time-ordered sequence of three-dimensional positions an aircraft follows from takeoff to landing, and can be described mathematically by a time-ordered set of trajectory vectors. In contrast, the flight plan of an aircraft will be referred to as information—either physical documents or electronic—that is filed by a pilot or a flight dispatcher with the local civil aviation authority prior to departure, and include such information as departure and arrival points, estimated time en route, and other general information that can be used by air traffic control (ATC) to provide tracking and routing services. Included in the concept of flight trajectory is that there is a trajectory path having a centerline, and position and time uncertainties surrounding this centerline. Trajectory synchronization may be defined as a process of resolving discrepancies between different representations of an aircraft's trajectory, such that any remaining differences are operationally insignificant. What constitutes an operationally insignificant difference depends on the intended use of the trajectory. Relatively larger differences may be acceptable for strategic demand estimates, whereas the differences must be much smaller for use in tactical separation management.
An overarching goal of TBO is to reduce the uncertainty associated with an aircraft's future location through use of an accurate four-dimensional trajectory (4DT) in space (latitude, longitude, altitude) and time. The use of precise 4DTs resulting from improved trajectory predictions has the ability to dramatically reduce the uncertainty of an aircraft's future flight path, including the ability to predict arrival times at a geographic location (referred to as metering fix, arrival fix, or cornerpost) for a group of aircraft that are approaching their arrival airport. Such a capability represents a significant change from the present “clearance-based control” approach (which depends on observations of an aircraft's current state) to a trajectory-based control approach, with the goal of allowing an aircraft to fly along a user-preferred trajectory. Thus, a critical enabler for TBO is not only the availability of an accurate, planned trajectory (or possibly multiple trajectories) and providing ATC with valuable information to allow more effective use of airspace, but also more accurate trajectory predictors that, if used in conjunction with appropriate Decision Support Tools (DSTs), would allow ATC to trial-plan different alternative solutions to address requests filed by airspace users while meeting ATC constraints. Another enabler of TBO is the ability to exchange data between aircrafts and ground. Several air-ground communication protocols and avionics performance standards exist or are under development, for example, controller pilot data link communication (CPDLC) and automatic dependent surveillance-contract (ADSC) technologies.
There exist a number of trajectory modeling and trajectory prediction frameworks and tools that have been proposed and that are currently in use in automation systems in air and on the ground, for instance, those described in WO 2009/042405 A2 entitled “Predicting Aircraft Trajectory,” U.S. Pat. No. 7,248,949 entitled “System and Method for Stochastic Aircraft Flight-Path Modeling,” and U.S. 2006/0224318 A1 entitled “Trajectory Prediction.” However, these trajectory modeling and trajectory prediction methods and systems do not disclose any capabilities for deriving or inferring parameters that are not available or known in explicit form, yet would be needed by trajectory predictors to achieve a higher degree of prediction accuracy. Improved prediction accuracies require better knowledge of the performance characteristics of an aircraft. However, in some cases, performance information cannot be shared directly with ground automation because of concerns related to information that is considered strategic and proprietary to the operator. Two typical examples of this category are aircraft weight and cost index. In other cases, the bandwidth of air-ground communication systems used to communicate relevant performance parameters is often constrained.
Other significant gaps remain in implementing TBO, due in part to the lack of validation activities and benefits assessments. In response, the General Electric Company and the Lockheed Martin Corporation have created a Joint Strategic Research Initiative (JSRI), which aims to generate technologies intended to accelerate the adoption of TBO in the Air Traffic Management (ATM) realm. Efforts of the JSRI have included the use of GE's Flight Management System (FMS) and aircraft expertise and the use of Lockheed Martin's ATC domain expertise, including the En Route Automation Modernization (ERAM) and the Common Automated Radar Terminal System (Common ARTS), to explore and evaluate trajectory negotiation and synchronization concepts. Ground automation systems typically provide trajectory predictors capable of predicting the paths of aircraft in time and space, providing information that is required for planning and performing critical air traffic control and traffic flow management functions, such as scheduling, conflict prediction, separation management and conformance monitoring. On board an aircraft, the FMS can use a trajectory for closed-loop guidance by way of the automatic flight control system (AFCS) of the aircraft. Many modern FMSs are also capable of meeting a required time-of-arrival (RTA), which may be assigned to an aircraft by ground systems.
Notwithstanding the above technological capabilities, questions remain related to Trajectory-Based Operations, including the manner in which parameters needed by trajectory predictors may be obtained from available information, for instance, from downlinked information, to guarantee an efficient air traffic control process where users meet their business objectives while fully honoring all ATC objectives (safe separation, traffic flow, etc.). In particular, there is a need for enabling ground automation systems to increase their prediction accuracy by having the ability to obtain key parameters used by the trajectory predictor, for instance, those related to an aircraft's performance. However, aircraft and engine manufacturers consider detailed aircraft performance data proprietary and commercially sensitive, which may limit the availability of detailed and accurate aircraft performance data for ground automation systems. Moreover, the aircraft thrust, drag, and fuel flow characteristics can vary significantly based on the age of the aircraft and time since maintenance, which ground automation systems will likely not know or be able to explicitly obtain. In some cases, aircraft performance information, such as gross weight and cost index, cannot be shared directly with ground automation because of concerns related to information that is considered strategic and proprietary to the operator. Even if these performance parameters were shared directly, because the aircraft performance model used by the aircraft and ground automation systems may be significantly different, they may actually decrease the accuracy of the ground trajectory prediction if used directly.
In addition to the above, the ability of ground automation systems to increase their prediction accuracy is further complicated by increasing levels of air traffic combined with the need to support more efficient airspace operations, the impact of potential revisions in the aircraft flight plan or airspace constraints, and constraints on bandwidth for communicating relevant performance parameters.